The Public Venture : How public resources will revolutionize data
markets and information retrieval.
I show how centralized sources, obscured by secrets and
limitations, are not the future of finding information.
I see technology allowing large data sets to be interoperable, to
effectively merge, while I forsee the underlying business interests and
markets on a course to fragmentation into various components of the
info retrieval process. (crawling, indexing, aggregating, categorizing, sorting, filters and interfaces)
I give an idea of what the world might be like if social network
profiles began to use a system of publishing now used by blogs. T
his would be a more 'open' and free form of mass publication, due
to the non-exclusive role of large publishers to control their medium.
I shows how in his world, the popular social networking activity
would never be able to be acquired or controlled.
I no longer see the social network services delivered by the current
giants as remaining the "destination" for their users. They will be
reduced to just a few of the many tools people use to reach and
communicate with the larger outside databases - The SocialSphere.
This doesn't mean that these companies won't be wildly successful as media companies, it
means that their power as exclusive social networks is inherently unstable, and they will constantly
have to re-define themselves.
Myspace will always be a successful web destination, but it's focus on
core social networking will have to get less and less, (just like
Google's focus on search)
Google says it's core is 70% search, but I think most of that is
advertising research and optimization. This clearly has it's place, but
Google has realized that to improve their search DRASTICALLY, would be to
admit there is a DRASTIC problem with their current technique.
Myspace will be the new MTV, with pretty faces, new studio promotions
and large brand atmosphere.
The users will remain, but will begin using more powerful tools to go
beyond only the myspace experience.
There is one area of innovation that large markets like Google and
Myspace cannot even go near.
That is the market of becoming part of a larger world of information
sharing.
Current, each social network is a gated community.
Even if membership is open, you can only search and see information
from ONE site, ONE database.
This means that if myspace doesn't get around to implement a feature,
it won't happen.
Even if the feature takes less than 1 hour of computer coder time.
Google will lose relevance as far as aggregating documents and lose some prominence in search, but will remain highly successful at incubating other internet properties, primarily in web media, and probably not as much in web widgets.
The reason is that anyone can make widgets, but not everyone can make
large media acquisitions which place themselves as or with large publsher networks and advertiser demand.
So, now google will remain strong from their cash position, and their
media portfolio, as well as their technological eminance as a data
processor.
Google will have an exciting future as a company, more focused on
advertising and media in the future rather than web document search.
Web search will continue to get more corporatized, with larger and more
numerous advertising placements. If a paid placement program was to
ever occur for indexing as it does with Yahoo's paid inclusion, it would
mean the end of the Google resource as we know it.
Evolving advertising trends suggest advertisers will begin to track the entire search experience, along with
email, social networking and video viewing experience to optimize campaigns
just for YOU.
Top 12 things Google will never do.
1. Google won't ever know what it's searching.
No conceptual understanding. No categorization scheme. Google doesn’t discern between fiction, nonfiction, reference, age-appropriate material, ...
2. Google will never understand what your intent was from your keyword. It can't understand the context or purpose of a search from just symbols alone. It has no conceputal framework.
Can't refine based on conceptual query intent, not keyword. Offers no way to refine search.
Does "baseball" mean the "game", the "league" (MLB), or the "ball"? It
is used in all of these contexts interchangably.
3. Can't learn from users, or let users use groups to filter. The goal of 'making the world's information accessible, may be noble, but unlessy ou open the system to
LET OTHER make the world's information structured and accessable, it's going to remain a artificially "intelligent" GAME. - Feeling lucky?
4. No privacy, one company masses all data and sells or uses the data on its own.
5. Ownership and Control
Censorship.
Advertising corrupting experience or results.
Market position inhibits integration, and possibilities.
Non-monopoly status of search, and publishing industries.
By contrast, the Benefits of an Open Platform - open data, open summaries, open relevance scores,
sorts and filters.
Customization, Upgrades, Flexibility
More competitive markets
Interoperability
Non-monopoly status of search, and publishing industries.
Everyone gets to use the cool toys at the Googleplex.
6. Never complete search of all libraries.
If Google can't find it, forget about it. They won't point you in the direction of another resource that is known to have good results
for your kind of query. Google doesn't summarize other rich resources. They try to be the one resource. They can't admit their limitations.
Even Yahoo would direct you to another engine if your query gave no results.
You need to admit when another resource has better results. Google is too centered around 'documents' and not enough on resources as a whole.
7. Always prone to spam, manipulation through data, manipulation with
money, non-first-rate resources by design.
There is bad spam, and then there is manipualation of results that are somehow approved, like buying web sites , buying links, doing PR stunts.
Does this lead to better results? Or just more "competitive" ones?
8. No authority, or authenticity, or certainty. Everything is just a
guesswork, probability, mass voting, mob rule, educated guesses. They
give you up to millions of results, because, you AREN'T feeling lucky.
I can't even trust which mob I want to rule my results? I'm stuck with the largest mob.
9. Advertising Banditry. Publishers don't know how much they make.
Click fraud rampant. CPC model ensures advertisers pay the most. But,
publisher sees little of this.
Adsense inefficiencies.
10. Made only to search unstructured data; Can't understand structured
knowledge.
Google's intent, and very assumption for it to work, is that it knows NOTHING about what it is searching in AND what it is searching for.
Google was made to sort the structureless web. It's great at that, but the structureless web sucks.
11. Only designed to crawl the outer web. The inner web is uncrawled.
Other applications of distributed computing:
Anti-manipulation, Pro-accountability in areas of
Accounting
Elections
Trade
Google is a tool, not an answer. It's initial results, in aggregate,
are valueless without human sifting afterwards.
The environment that created Google was one of total lack of
cohesiveness to the web.
Google Needs a Dewey Decimal System
Google's algorithm is already very useful for what it does - Delivers
likely possible solutions to what might have been the intent of your
search.
It will always be good at that, and continue to get better at doing
JUST THAT.
But, without a dewey-decimal-like system, it falls short as an
information retrieval ideology.
Google as ideology fails when it cannot realize that the world's
library belongs to the world; not to private advertisers or a small band of dorks. Or information
hogs. Or media giants. Or software companies.
In, Of, and By the Public this Library will be.
Benefits of Distributed system.
In a purely technical sense, the distribted system does not directly
make search better, in and of itself.
It allows search to become better indirectly by making the development
of search filters and classification systems to be developed and shared
by everyone in a standard and low-cost environ.
Aggregating resources is extremely easy with this system architecture.
This will encourage many current web publishers to adopt rigorous niche
classification systems that fit into larger-scope Labeling systems.
It also lowers the cost of innovation in all aspects of the search
process, by making crawling obsolete, and by making aggregation of
resources a technologically trivial process (even if it is still a complex and
multifarious process in terms of the taxonomy, the
"code work" and interfaces are all taken care of. There will be various
competing providers of the classification schemes, and the markets will
decide what ones thrive. The architecture allows these to be made
available to the user.
In the exact same vein, it opens the market for enhanced providers of
filters and algorithms, and various processes that sort, map, and
predictively analyze the result sets imported from other tools.
In this way, the distributed system greatly changes the economics of
the many search engine development areas.
By isolating the various components of the "search engine', this new
system will foster greater customization and innovation - The components
being the aggregation, the relevance processes (either symbolic,
conceptual, authoriative, socially computed, or a blend) and the sorting and
filtering algorithms.
The distributed system also changes the politics of search indexes,
social networks, and any kind of structured resource.
The current system does not aid those that seek exhaustive,
authoritative, definative document sets...not sets of possible matches.
When the search result set represents a complete, spam-free, and is
clear of off-topic content, then it can be seen as a datum in and of
itself.
It becomes an index, of a certian kind of query intent.
This datum then can be meaningfully combined, or summarized and
combined with other complimentary, or supplimentary resources to allow this
strucuted index to be used by other resources to provide greated depth
and breadth to the search experience.
As long as there is still noise and potentially bad results, Google's results don't represent knowledge.
The user has to turn that information into knowledge by going through and evaluating the results.
The other fundamental limitation of Google is it's ignorance of the
intent of the searcher.
When searching for "jaguar", it gives some possible document lists.
But, to result of the "relevance" process, and the sorting process
cannot be considered aything but an attempt at possible relevance.
The sorting the results as a SET in this case is informationally
valueless, because the results collect from various contexts of the term -
the cat, the car, the sportsclub.
Its true that a subset of the results represent value to that searcher.
But it is the laborious job of the searcher to define that subset for
himself, unfortunately one document at a time. And, worst of all, even
after the searcher has essentially sorted the search results based on
relevancy for his intent, the information is usually uncaptured, or
completely lost, and even the implicit indirect clues lying in
user-behaviour that could be used to corrolate to the user's intent and satisfaction
with the results are horded by a company that can't benefit from it's
value, due to it's antiquated strategic central position as aggregator.
So, it is definately the classification that is the largest improvement
of all.
The distributed platform doesn't directly offer any solution itself to
classify all objects by mechanical processes.
But, it does allow systems of communication by PEOPLE, who after all
are the final judge of the merit of a search results for a query intent.
The searcher is the final judge of relevancy, why not make them the
primary judge?
After all, keyword density, pagerank, anchor links, are only
CORROLATIONS with authority and usefullness, they do not represent usefulness
themselves.
And, the more the rigid rules are made apparent to manipulators, the more they can
be gamed in that fashion.
Google suffers an adversarial classificaiton problem, there's always a
way in - spam, or investment in white hat SEO.
By lowering costs to build ontologies, (the dewey decimal systems of
tomorrow), and advanced search processes and filters - distributed
indexing has an indirect and pronounced effect on search relevance and cost.
Crawling the web is now a redundant process. Just like other examples
of peer to peer technilogy making processes obsolete such as ripping
your own CD, when you can just download the MP3 from a p2p network.
Storing for the first time is done. Its just re-getting, finding from one of
many shared resources.
Looking beyond the page -
References - Google only makes it's final sorting decision based on
popularity, not the degree to which a document references other
authoritative sources.
That means a document that is highly referenced will have priority over
those that are not.
All else being equal, this is a good technique for determining a
corrolation to authority.
Some searchers may only want to search sources that themselves are well
documented, well-cited, and employ rich sets of references within their
document.
Having references within their document, to other authoritative
documents is a corrolation not only with relevance, but also authority in the
true sense of the word.
It is true that Google does give some benefit to those linking out to
sites with Good trust rank, and that outgoing links can effect the SEO
results, but this is more of a way to avoid the spam filter than
something that will cause a surge in the rankings.
Basically, there is no way for the searcher to specify the preference for rich
references in the documents they search. This is a limitation.
Not all queries require a document heavy in citiations, but, with spam,
and shoddy content, made-for-AdSense pages, the option to filter
documents without citations and refences is a necessary one for true
knowledge retrievers.
Document Density (of Topics or Concepts)
Just as contemporary web "Page" based search engines use "keyword
density" to estimate or predict the likely relevance of a resulting page,
the new system of searching "resources" will be largely influenced by
that resources proportion of documents pertaining to the given topic.
For instance, one resource may have fewer overall results, but have
results almost completely dedicated to your intended information.
THis is certainly a more time-efficient resource to begin with, and
resources of this type make better resources for beginners and experts
(perhaps not the same ones, but denser resources will be better in both
instances)
Sparse resources will many times actually give more results.
Anyone who's gotten over 1 million Google results for a query probably
hadn't made time to go through them all, and probably realizes that
this would be useless.
Sparse results mean that although the resource contains results, since
it is a miniscule part of its document set, it is unlikely to have
well-structured indexes and supplemental indexes pertaining to the topic
and is also likely to lack useful query-intent clarification procedures
to your specific intent.
The sparse resource may have fewer results, or may have more results.
THe more results usually contain garbage, spam, and "lesser sources",
one that probably aren't worth of informational content, but are
on-topic nonetheless.
Even if the sparse collection contains truly more "good resources", the
fact that they are essentially HIDDEN in the result set with other junk
makes it a less valueable resource.
The dense sources have none of these distractions.
The sparse sources may have more 'good resources', but they don't have
any classification system, or sub-indicies, or query clarification
tools to let a person search with tools that pertain to their domain.
In a sense, sparse sourcss are just one area of a tangled web. The
larger tangled web isn't structured conceptually, and neither will be the
'good resource' page results, however numerous they are.
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